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data quality and compliance issues
accountability across data domains
To address inconsistent master data, Saxon helped implement a rules engine that enforces standards, validations, and governance across systems, improving data quality and analytics readiness.
By centralizing and governing product, customer, and sales master data within SAP, Saxon helped eliminate data inconsistencies and accelerate insight-driven decision-making.
Data governance includes defining ownership, policies, standards, and controls to ensure data quality, security, and compliance.
Data governance defines rules and accountability, while MDM focuses on standardizing core business entities.
Yes. Governance frameworks are designed to work across existing data and analytics platforms.
By embedding governance into data workflows and aligning ownership with business teams.
Yes. Governance models are designed to scale across domains, teams, and systems.